Systems and methods for customized processing and visualization of data

Abstract

A method may include receiving tabular data and receiving a first user input of a description of the tabular data and a second user input of a recipient of the tabular data or a report to be generated based on the tabular data. The method may include converting the tabular data to a text-based language to form converted tabular data and performing, using one or more first machine learning models, pre-processing of the converted tabular data. The method may include applying one or more second machine learning models to the converted tabular data based on the description, the recipient, a context of the converted tabular data, or a characteristic of the converted tabular data. The method may include performing one or more actions based on a result of applying the one or more second machine learning models.

What is claimed is: 
     
         1 . A computer-implemented method for customized processing and visualization of data, comprising:
 receiving, by a server device, tabular data;   receiving a first user input of a description of the tabular data and a second user input of a recipient of the tabular data or a report to be generated based on the tabular data;   converting the tabular data to a text-based language to form converted tabular data;   performing, using one or more first machine learning models, pre-processing of the converted tabular data based on the description or the recipient, wherein different first machine learning models have been trained to perform different pre-processing operations for different descriptions or different recipients;   applying one or more second machine learning models to the converted tabular data based on the description, the recipient, a context of the converted tabular data, or a characteristic of the converted tabular data, wherein different second machine learning models have been trained and are applied for the different descriptions, the different recipients, different contexts, different characteristics, or different visualizations; and   performing one or more actions based on a result of applying the one or more second machine learning models, the one or more actions including:
 providing a virtual dashboard to visualize the converted tabular data or the result, and 
 generating one or more reports for the converted tabular data or the result. 
   
     
     
         2 . The method according to  claim 1 , wherein the converting of the tabular data further comprises:
 converting the tabular data to a JavaScript Object Notation (JSON) format or an extensible markup language (XML) format.   
     
     
         3 . The method according to  claim 1 , further comprising:
 selecting the one or more first machine learning models from multiple possible first machine learning models based on the description or the recipient; and   wherein the performing of the pre-processing further comprises:
 performing the pre-processing using the one or more selected first machine learning models. 
   
     
     
         4 . The method according to  claim 1 , further comprising:
 selecting the one or more second machine learning models based on the description, the recipient, the context, or the characteristic; and   wherein the applying of the one or more second machine learning models further comprises:
 applying the one or more selected second machine learning models. 
   
     
     
         5 . The method according to  claim 1 , wherein the performing of the pre-processing further comprises:
 applying a formatting to the converted tabular data.   
     
     
         6 . The method according to  claim 1 , wherein the applying of the one or more second machine learning models further comprises:
 processing the converted tabular data to perform a calculation or an analysis.   
     
     
         7 . The method according to  claim 1 , wherein the one or more actions further comprise:
 sending a message that includes the one or more generated reports, or   storing the one or more generated reports.   
     
     
         8 . The method according to  claim 1 , wherein the one or more actions further comprise:
 determining one or more individuals to attend a meeting based on the one or more generated reports or a result of the applying of the one or more second machine learning models.   
     
     
         9 . The method according to  claim 8 , further comprising:
 scheduling the meeting for the one or more individuals;   generating a calendar invite for the meeting; and   sending the calendar invite to user devices associated with the one or more individuals.   
     
     
         10 . The method according to  claim 1 , further comprising:
 providing a user interface for display via a user device; and   wherein the receiving of the tabular data further comprises:
 receiving the tabular data as a file upload via the user interface. 
   
     
     
         11 . A server device, comprising:
 at least one memory storing instructions; and   at least one processor executing the instructions to perform operations for customized processing and visualization of data, the operations including:   receiving tabular data;   receiving a first user input of a description of the tabular data and a second user input of a recipient of the tabular data or a report to be generated based on the tabular data;   converting the tabular data to a text-based language to form converted tabular data;   performing, using one or more first machine learning models, pre-processing of the converted tabular data based on the description or the recipient, wherein different first machine learning models have been trained to perform different pre-processing operations for different descriptions or different recipients;   applying one or more second machine learning models to the converted tabular data based on the description, the recipient, a context of the converted tabular data, or a characteristic of the converted tabular data, wherein different second machine learning models have been trained and are applied for the different descriptions, the different recipients, different contexts, different characteristics, or different visualizations; and   performing one or more actions based on a result of applying the one or more second machine learning models, the one or more actions including:
 providing a virtual dashboard to visualize the converted tabular data or the result, and 
 generating one or more reports for the converted tabular data or the result. 
   
     
     
         12 . The server device according to  claim 11 , wherein the converting of the tabular data further comprises:
 converting the tabular data to a JavaScript Object Notation (JSON) format or an extensible markup language (XML) format.   
     
     
         13 . The server device according to  claim 11 , wherein the operations further comprise:
 selecting the one or more first machine learning models from multiple possible first machine learning models based on the description or the recipient; and   wherein the performing of the pre-processing further comprises:
 performing the pre-processing using the one or more selected first machine learning models. 
   
     
     
         14 . The server device according to  claim 11 , wherein the operations further comprise selecting the one or more second machine learning models based on the description, the recipient, the context, or the characteristic; and
 wherein the applying of the one or more second machine learning models further comprises:
 applying the one or more selected second machine learning models. 
   
     
     
         15 . The server device according to  claim 11 , wherein the performing of the pre-processing further comprises:
 applying a formatting to the converted tabular data.   
     
     
         16 . The server device according to  claim 11 , wherein the applying of the one or more second machine learning models further comprises:
 processing the converted tabular data to perform a calculation or an analysis.   
     
     
         17 . The server device according to  claim 11 , wherein the one or more actions further comprise:
 sending a message that includes the one or more generated reports, or   storing the one or more generated reports.   
     
     
         18 . The server device according to  claim 11 , wherein the one or more actions further comprise:
 determining one or more individuals to attend a meeting based on the one or more generated reports or a result of the applying of the one or more second machine learning models.   
     
     
         19 . The server device according to  claim 18 , wherein the operations further comprise:
 scheduling the meeting for the one or more individuals;   generating a calendar invite for the meeting; and   sending the calendar invite to user devices associated with the one or more individuals.   
     
     
         20 . A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to perform a method for customized processing and visualization of data, the method comprising:
 receiving tabular data;   receiving a first user input of a description of the tabular data and a second user input of a recipient of the tabular data or a report to be generated based on the tabular data;   converting the tabular data to a text-based language to form converted tabular data;   performing, using one or more first machine learning models, pre-processing of the converted tabular data based on the description or the recipient, wherein different first machine learning models have been trained to perform different pre-processing operations for different descriptions or different recipients;   applying one or more second machine learning models to the converted tabular data based on the description, the recipient, a context of the converted tabular data, or a characteristic of the converted tabular data, wherein different second machine learning models have been trained and are applied for the different descriptions, the different recipients, different contexts, different characteristics, or different visualizations; and   performing one or more actions based on a result of applying the one or more second machine learning models, the one or more actions including:
 providing a virtual dashboard to visualize the converted tabular data or the result, and 
 generating one or more reports for the converted tabular data or the result.